{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>report_date</th>\n",
       "      <th>tBalance</th>\n",
       "      <th>yBalance</th>\n",
       "      <th>total_purchase_amt</th>\n",
       "      <th>direct_purchase_amt</th>\n",
       "      <th>purchase_bal_amt</th>\n",
       "      <th>purchase_bank_amt</th>\n",
       "      <th>total_redeem_amt</th>\n",
       "      <th>consume_amt</th>\n",
       "      <th>transfer_amt</th>\n",
       "      <th>tftobal_amt</th>\n",
       "      <th>tftocard_amt</th>\n",
       "      <th>share_amt</th>\n",
       "      <th>category1</th>\n",
       "      <th>category2</th>\n",
       "      <th>category3</th>\n",
       "      <th>category4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-08-05</td>\n",
       "      <td>20385</td>\n",
       "      <td>20383</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-08-08</td>\n",
       "      <td>20391</td>\n",
       "      <td>20389</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-08-11</td>\n",
       "      <td>20397</td>\n",
       "      <td>20395</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-08-14</td>\n",
       "      <td>20403</td>\n",
       "      <td>20401</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2014-08-17</td>\n",
       "      <td>20409</td>\n",
       "      <td>20407</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840416</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-08-25</td>\n",
       "      <td>550646</td>\n",
       "      <td>550585</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840417</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-08-31</td>\n",
       "      <td>525707</td>\n",
       "      <td>538147</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12500</td>\n",
       "      <td>12500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840418</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-24</td>\n",
       "      <td>20487121</td>\n",
       "      <td>20484824</td>\n",
       "      <td>2297</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840419</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-27</td>\n",
       "      <td>20462288</td>\n",
       "      <td>20491722</td>\n",
       "      <td>2298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>2298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840420</th>\n",
       "      <td>28035</td>\n",
       "      <td>2014-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2840421 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id report_date  tBalance  yBalance  total_purchase_amt  \\\n",
       "0              1  2014-08-05     20385     20383                   2   \n",
       "1              1  2014-08-08     20391     20389                   2   \n",
       "2              1  2014-08-11     20397     20395                   2   \n",
       "3              1  2014-08-14     20403     20401                   2   \n",
       "4              1  2014-08-17     20409     20407                   2   \n",
       "...          ...         ...       ...       ...                 ...   \n",
       "2840416    28033  2014-08-25    550646    550585                  61   \n",
       "2840417    28033  2014-08-31    525707    538147                  60   \n",
       "2840418    28033  2014-07-24  20487121  20484824                2297   \n",
       "2840419    28033  2014-07-27  20462288  20491722                2298   \n",
       "2840420    28035  2014-03-05         0         0                   0   \n",
       "\n",
       "         direct_purchase_amt  purchase_bal_amt  purchase_bank_amt  \\\n",
       "0                          0                 0                  0   \n",
       "1                          0                 0                  0   \n",
       "2                          0                 0                  0   \n",
       "3                          0                 0                  0   \n",
       "4                          0                 0                  0   \n",
       "...                      ...               ...                ...   \n",
       "2840416                    0                 0                  0   \n",
       "2840417                    0                 0                  0   \n",
       "2840418                    0                 0                  0   \n",
       "2840419                    0                 0                  0   \n",
       "2840420                    0                 0                  0   \n",
       "\n",
       "         total_redeem_amt  consume_amt  transfer_amt  tftobal_amt  \\\n",
       "0                       0            0             0            0   \n",
       "1                       0            0             0            0   \n",
       "2                       0            0             0            0   \n",
       "3                       0            0             0            0   \n",
       "4                       0            0             0            0   \n",
       "...                   ...          ...           ...          ...   \n",
       "2840416                 0            0             0            0   \n",
       "2840417             12500        12500             0            0   \n",
       "2840418                 0            0             0            0   \n",
       "2840419             31732            0         31732            0   \n",
       "2840420                 0            0             0            0   \n",
       "\n",
       "         tftocard_amt  share_amt  category1  category2  category3  category4  \n",
       "0                   0          2        NaN        NaN        NaN        NaN  \n",
       "1                   0          2        NaN        NaN        NaN        NaN  \n",
       "2                   0          2        NaN        NaN        NaN        NaN  \n",
       "3                   0          2        NaN        NaN        NaN        NaN  \n",
       "4                   0          2        NaN        NaN        NaN        NaN  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2840416             0         61        NaN        NaN        NaN        NaN  \n",
       "2840417             0         60        0.0        0.0        0.0    12500.0  \n",
       "2840418             0       2297        NaN        NaN        NaN        NaN  \n",
       "2840419         31732       2298        NaN        NaN        NaN        NaN  \n",
       "2840420             0          0        NaN        NaN        NaN        NaN  \n",
       "\n",
       "[2840421 rows x 18 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 数据加载 parse_dates自动转换时间格式\n",
    "data = pd.read_csv('user_balance_table.csv',parse_dates=['report_date'])\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-2-188ca9d35da2>:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  total_balance = data.groupby('report_date')['total_purchase_amt','total_redeem_amt'].sum()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt  total_redeem_amt\n",
       "report_date                                      \n",
       "2013-07-01             32488348           5525022\n",
       "2013-07-02             29037390           2554548\n",
       "2013-07-03             27270770           5953867\n",
       "2013-07-04             18321185           6410729\n",
       "2013-07-05             11648749           2763587\n",
       "...                         ...               ...\n",
       "2014-08-27            302194801         468164147\n",
       "2014-08-28            245082751         297893861\n",
       "2014-08-29            267554713         273756380\n",
       "2014-08-30            199708772         196374134\n",
       "2014-08-31            275090213         292943033\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_balance = data.groupby('report_date')['total_purchase_amt','total_redeem_amt'].sum()\n",
    "total_balance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_redeem_amt\n",
       "report_date                  \n",
       "2013-07-01            5525022\n",
       "2013-07-02            2554548\n",
       "2013-07-03            5953867\n",
       "2013-07-04            6410729\n",
       "2013-07-05            2763587\n",
       "...                       ...\n",
       "2014-08-27          468164147\n",
       "2014-08-28          297893861\n",
       "2014-08-29          273756380\n",
       "2014-08-30          196374134\n",
       "2014-08-31          292943033\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purchase = total_balance[['total_purchase_amt']]\n",
    "redeem = total_balance[['total_redeem_amt']]\n",
    "redeem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "# 对指定区间范围内的数据，进行可视化\n",
    "def plot_stl(data):\n",
    "    # STL返回三个部分：trend(趋势)，seasonal(季节)，residual(残差)\n",
    "    result = sm.tsa.seasonal_decompose(data, period=30)\n",
    "    # 可视化\n",
    "    fig = plt.figure(figsize=(12, 8))\n",
    "    ax1 = fig.add_subplot(311)\n",
    "    ax2 = fig.add_subplot(312)\n",
    "    ax3 = fig.add_subplot(313)\n",
    "    \n",
    "    result.trend.plot(ax=ax1, title='Trend')\n",
    "    result.seasonal.plot(ax=ax2,title='Seasonal')\n",
    "    result.resid.plot(ax=ax3,title='Residual')\n",
    "\n",
    "plot_stl(purchase.total_purchase_amt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "purchase2 = purchase[(purchase.index >= '2014-04-01') & (purchase.index <= '2014-04-30')]\n",
    "# 画出走势图\n",
    "plt.figure(figsize=(20, 10))\n",
    "plt.plot(purchase2.total_purchase_amt)\n",
    "date_range = pd.date_range('2014-04-01','2014-04-30')\n",
    "# plt.xticks(date_range, rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.5898802926313496,\n",
       " 0.48867497513759334,\n",
       " 18,\n",
       " 408,\n",
       " {'1%': -3.446479704252724,\n",
       "  '5%': -2.8686500930967354,\n",
       "  '10%': -2.5705574627547096},\n",
       " 15960.28197033403)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 看时间序列的平稳性\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "t = adfuller(purchase['total_purchase_amt'])\n",
    "t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-1.5898..比10%的还要大，所以不能拒绝原假设，所以，差分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-7.947102224652337,\n",
       " 3.198186862488301e-12,\n",
       " 18,\n",
       " 407,\n",
       " {'1%': -3.4465195891135845,\n",
       "  '5%': -2.8686676281678634,\n",
       "  '10%': -2.5705668101226085},\n",
       " 15918.844657651942)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff1 = purchase.diff(1)\n",
    "t = adfuller(diff1[1:])\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\学习\\研究生\\算法工程师\\Bi\\Bi_env\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:524: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  warnings.warn('No frequency information was'\n",
      "d:\\学习\\研究生\\算法工程师\\Bi\\Bi_env\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:524: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  warnings.warn('No frequency information was'\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2014-09-01    3.310533e+08\n",
       "2014-09-02    3.318762e+08\n",
       "2014-09-03    3.338908e+08\n",
       "2014-09-04    2.983202e+08\n",
       "2014-09-05    2.407518e+08\n",
       "2014-09-06    2.266145e+08\n",
       "2014-09-07    2.435559e+08\n",
       "2014-09-08    2.970859e+08\n",
       "2014-09-09    3.321273e+08\n",
       "2014-09-10    3.265198e+08\n",
       "2014-09-11    2.916847e+08\n",
       "2014-09-12    2.392714e+08\n",
       "2014-09-13    2.253553e+08\n",
       "2014-09-14    2.475291e+08\n",
       "2014-09-15    2.950930e+08\n",
       "2014-09-16    3.345005e+08\n",
       "2014-09-17    3.280821e+08\n",
       "2014-09-18    2.927104e+08\n",
       "2014-09-19    2.448979e+08\n",
       "2014-09-20    2.275716e+08\n",
       "2014-09-21    2.530229e+08\n",
       "2014-09-22    2.980714e+08\n",
       "2014-09-23    3.366740e+08\n",
       "2014-09-24    3.321950e+08\n",
       "2014-09-25    2.947112e+08\n",
       "2014-09-26    2.505394e+08\n",
       "2014-09-27    2.318276e+08\n",
       "2014-09-28    2.574469e+08\n",
       "2014-09-29    3.025697e+08\n",
       "2014-09-30    3.387011e+08\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "# p,d,q其中d=1\n",
    "model = ARIMA(purchase, order=(7,1,5)).fit()\n",
    "# 使用typ='levels' 对原始数据维度上进行预测，相当于进行了反差分\n",
    "purchase_pred = model.predict('2014-09-01','2014-09-30', typ = 'levels')\n",
    "purchase_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\学习\\研究生\\算法工程师\\Bi\\Bi_env\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:524: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  warnings.warn('No frequency information was'\n",
      "d:\\学习\\研究生\\算法工程师\\Bi\\Bi_env\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:524: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  warnings.warn('No frequency information was'\n",
      "d:\\学习\\研究生\\算法工程师\\Bi\\Bi_env\\lib\\site-packages\\statsmodels\\base\\model.py:566: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2014-09-01    3.169695e+08\n",
       "2014-09-02    3.372864e+08\n",
       "2014-09-03    3.631589e+08\n",
       "2014-09-04    3.073744e+08\n",
       "2014-09-05    2.627309e+08\n",
       "2014-09-06    2.259098e+08\n",
       "2014-09-07    2.593021e+08\n",
       "2014-09-08    3.116524e+08\n",
       "2014-09-09    3.477937e+08\n",
       "2014-09-10    3.561747e+08\n",
       "2014-09-11    3.091838e+08\n",
       "2014-09-12    2.597762e+08\n",
       "2014-09-13    2.339488e+08\n",
       "2014-09-14    2.579362e+08\n",
       "2014-09-15    3.126721e+08\n",
       "2014-09-16    3.537815e+08\n",
       "2014-09-17    3.572977e+08\n",
       "2014-09-18    3.145101e+08\n",
       "2014-09-19    2.625816e+08\n",
       "2014-09-20    2.387781e+08\n",
       "2014-09-21    2.617507e+08\n",
       "2014-09-22    3.158567e+08\n",
       "2014-09-23    3.588732e+08\n",
       "2014-09-24    3.610879e+08\n",
       "2014-09-25    3.196666e+08\n",
       "2014-09-26    2.671166e+08\n",
       "2014-09-27    2.433172e+08\n",
       "2014-09-28    2.662621e+08\n",
       "2014-09-29    3.198686e+08\n",
       "2014-09-30    3.636147e+08\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "# p,d,q其中d=1\n",
    "model2 = ARIMA(redeem, order=(7,1,5)).fit()\n",
    "# 使用typ='levels' 对原始数据维度上进行预测，相当于进行了反差分\n",
    "redeem_pred = model2.predict('2014-09-01','2014-09-30', typ = 'levels')\n",
    "redeem_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 5))\n",
    "plt.title('Purchase Prediction')\n",
    "plt.plot(purchase_pred)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.title('Redeem Prediction')\n",
    "plt.plot(redeem_pred)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>purchase</th>\n",
       "      <th>redeem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>3.310533e+08</td>\n",
       "      <td>3.169695e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-09-02</td>\n",
       "      <td>3.318762e+08</td>\n",
       "      <td>3.372864e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-09-03</td>\n",
       "      <td>3.338908e+08</td>\n",
       "      <td>3.631589e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-09-04</td>\n",
       "      <td>2.983202e+08</td>\n",
       "      <td>3.073744e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-09-05</td>\n",
       "      <td>2.407518e+08</td>\n",
       "      <td>2.627309e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2014-09-06</td>\n",
       "      <td>2.266145e+08</td>\n",
       "      <td>2.259098e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>2.435559e+08</td>\n",
       "      <td>2.593021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014-09-08</td>\n",
       "      <td>2.970859e+08</td>\n",
       "      <td>3.116524e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014-09-09</td>\n",
       "      <td>3.321273e+08</td>\n",
       "      <td>3.477937e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014-09-10</td>\n",
       "      <td>3.265198e+08</td>\n",
       "      <td>3.561747e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014-09-11</td>\n",
       "      <td>2.916847e+08</td>\n",
       "      <td>3.091838e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014-09-12</td>\n",
       "      <td>2.392714e+08</td>\n",
       "      <td>2.597762e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014-09-13</td>\n",
       "      <td>2.253553e+08</td>\n",
       "      <td>2.339488e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>2.475291e+08</td>\n",
       "      <td>2.579362e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>2.950930e+08</td>\n",
       "      <td>3.126721e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>3.345005e+08</td>\n",
       "      <td>3.537815e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>3.280821e+08</td>\n",
       "      <td>3.572977e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.927104e+08</td>\n",
       "      <td>3.145101e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>2.448979e+08</td>\n",
       "      <td>2.625816e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>2.275716e+08</td>\n",
       "      <td>2.387781e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>2.530229e+08</td>\n",
       "      <td>2.617507e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2.980714e+08</td>\n",
       "      <td>3.158567e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>3.366740e+08</td>\n",
       "      <td>3.588732e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014-09-24</td>\n",
       "      <td>3.321950e+08</td>\n",
       "      <td>3.610879e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2014-09-25</td>\n",
       "      <td>2.947112e+08</td>\n",
       "      <td>3.196666e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.505394e+08</td>\n",
       "      <td>2.671166e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>2.318276e+08</td>\n",
       "      <td>2.433172e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>2.574469e+08</td>\n",
       "      <td>2.662621e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>3.025697e+08</td>\n",
       "      <td>3.198686e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>3.387011e+08</td>\n",
       "      <td>3.636147e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date      purchase        redeem\n",
       "0  2014-09-01  3.310533e+08  3.169695e+08\n",
       "1  2014-09-02  3.318762e+08  3.372864e+08\n",
       "2  2014-09-03  3.338908e+08  3.631589e+08\n",
       "3  2014-09-04  2.983202e+08  3.073744e+08\n",
       "4  2014-09-05  2.407518e+08  2.627309e+08\n",
       "5  2014-09-06  2.266145e+08  2.259098e+08\n",
       "6  2014-09-07  2.435559e+08  2.593021e+08\n",
       "7  2014-09-08  2.970859e+08  3.116524e+08\n",
       "8  2014-09-09  3.321273e+08  3.477937e+08\n",
       "9  2014-09-10  3.265198e+08  3.561747e+08\n",
       "10 2014-09-11  2.916847e+08  3.091838e+08\n",
       "11 2014-09-12  2.392714e+08  2.597762e+08\n",
       "12 2014-09-13  2.253553e+08  2.339488e+08\n",
       "13 2014-09-14  2.475291e+08  2.579362e+08\n",
       "14 2014-09-15  2.950930e+08  3.126721e+08\n",
       "15 2014-09-16  3.345005e+08  3.537815e+08\n",
       "16 2014-09-17  3.280821e+08  3.572977e+08\n",
       "17 2014-09-18  2.927104e+08  3.145101e+08\n",
       "18 2014-09-19  2.448979e+08  2.625816e+08\n",
       "19 2014-09-20  2.275716e+08  2.387781e+08\n",
       "20 2014-09-21  2.530229e+08  2.617507e+08\n",
       "21 2014-09-22  2.980714e+08  3.158567e+08\n",
       "22 2014-09-23  3.366740e+08  3.588732e+08\n",
       "23 2014-09-24  3.321950e+08  3.610879e+08\n",
       "24 2014-09-25  2.947112e+08  3.196666e+08\n",
       "25 2014-09-26  2.505394e+08  2.671166e+08\n",
       "26 2014-09-27  2.318276e+08  2.433172e+08\n",
       "27 2014-09-28  2.574469e+08  2.662621e+08\n",
       "28 2014-09-29  3.025697e+08  3.198686e+08\n",
       "29 2014-09-30  3.387011e+08  3.636147e+08"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = pd.DataFrame()\n",
    "result['date'] = purchase_pred.index\n",
    "result['purchase'] = purchase_pred.values\n",
    "result['redeem'] = redeem_pred.values\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>purchase</th>\n",
       "      <th>redeem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20140901</td>\n",
       "      <td>3.310533e+08</td>\n",
       "      <td>3.169695e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20140902</td>\n",
       "      <td>3.318762e+08</td>\n",
       "      <td>3.372864e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20140903</td>\n",
       "      <td>3.338908e+08</td>\n",
       "      <td>3.631589e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20140904</td>\n",
       "      <td>2.983202e+08</td>\n",
       "      <td>3.073744e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20140905</td>\n",
       "      <td>2.407518e+08</td>\n",
       "      <td>2.627309e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20140906</td>\n",
       "      <td>2.266145e+08</td>\n",
       "      <td>2.259098e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20140907</td>\n",
       "      <td>2.435559e+08</td>\n",
       "      <td>2.593021e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20140908</td>\n",
       "      <td>2.970859e+08</td>\n",
       "      <td>3.116524e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20140909</td>\n",
       "      <td>3.321273e+08</td>\n",
       "      <td>3.477937e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20140910</td>\n",
       "      <td>3.265198e+08</td>\n",
       "      <td>3.561747e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20140911</td>\n",
       "      <td>2.916847e+08</td>\n",
       "      <td>3.091838e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20140912</td>\n",
       "      <td>2.392714e+08</td>\n",
       "      <td>2.597762e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20140913</td>\n",
       "      <td>2.253553e+08</td>\n",
       "      <td>2.339488e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>20140914</td>\n",
       "      <td>2.475291e+08</td>\n",
       "      <td>2.579362e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>20140915</td>\n",
       "      <td>2.950930e+08</td>\n",
       "      <td>3.126721e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20140916</td>\n",
       "      <td>3.345005e+08</td>\n",
       "      <td>3.537815e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20140917</td>\n",
       "      <td>3.280821e+08</td>\n",
       "      <td>3.572977e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20140918</td>\n",
       "      <td>2.927104e+08</td>\n",
       "      <td>3.145101e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20140919</td>\n",
       "      <td>2.448979e+08</td>\n",
       "      <td>2.625816e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20140920</td>\n",
       "      <td>2.275716e+08</td>\n",
       "      <td>2.387781e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20140921</td>\n",
       "      <td>2.530229e+08</td>\n",
       "      <td>2.617507e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>20140922</td>\n",
       "      <td>2.980714e+08</td>\n",
       "      <td>3.158567e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>20140923</td>\n",
       "      <td>3.366740e+08</td>\n",
       "      <td>3.588732e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>20140924</td>\n",
       "      <td>3.321950e+08</td>\n",
       "      <td>3.610879e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>20140925</td>\n",
       "      <td>2.947112e+08</td>\n",
       "      <td>3.196666e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>20140926</td>\n",
       "      <td>2.505394e+08</td>\n",
       "      <td>2.671166e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>20140927</td>\n",
       "      <td>2.318276e+08</td>\n",
       "      <td>2.433172e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>20140928</td>\n",
       "      <td>2.574469e+08</td>\n",
       "      <td>2.662621e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>20140929</td>\n",
       "      <td>3.025697e+08</td>\n",
       "      <td>3.198686e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>20140930</td>\n",
       "      <td>3.387011e+08</td>\n",
       "      <td>3.636147e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date      purchase        redeem\n",
       "0   20140901  3.310533e+08  3.169695e+08\n",
       "1   20140902  3.318762e+08  3.372864e+08\n",
       "2   20140903  3.338908e+08  3.631589e+08\n",
       "3   20140904  2.983202e+08  3.073744e+08\n",
       "4   20140905  2.407518e+08  2.627309e+08\n",
       "5   20140906  2.266145e+08  2.259098e+08\n",
       "6   20140907  2.435559e+08  2.593021e+08\n",
       "7   20140908  2.970859e+08  3.116524e+08\n",
       "8   20140909  3.321273e+08  3.477937e+08\n",
       "9   20140910  3.265198e+08  3.561747e+08\n",
       "10  20140911  2.916847e+08  3.091838e+08\n",
       "11  20140912  2.392714e+08  2.597762e+08\n",
       "12  20140913  2.253553e+08  2.339488e+08\n",
       "13  20140914  2.475291e+08  2.579362e+08\n",
       "14  20140915  2.950930e+08  3.126721e+08\n",
       "15  20140916  3.345005e+08  3.537815e+08\n",
       "16  20140917  3.280821e+08  3.572977e+08\n",
       "17  20140918  2.927104e+08  3.145101e+08\n",
       "18  20140919  2.448979e+08  2.625816e+08\n",
       "19  20140920  2.275716e+08  2.387781e+08\n",
       "20  20140921  2.530229e+08  2.617507e+08\n",
       "21  20140922  2.980714e+08  3.158567e+08\n",
       "22  20140923  3.366740e+08  3.588732e+08\n",
       "23  20140924  3.321950e+08  3.610879e+08\n",
       "24  20140925  2.947112e+08  3.196666e+08\n",
       "25  20140926  2.505394e+08  2.671166e+08\n",
       "26  20140927  2.318276e+08  2.433172e+08\n",
       "27  20140928  2.574469e+08  2.662621e+08\n",
       "28  20140929  3.025697e+08  3.198686e+08\n",
       "29  20140930  3.387011e+08  3.636147e+08"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result['date'] = result['date'].apply(lambda x: str(x).replace('-','')[0:8])\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "result.to_csv('arima.csv', header=None, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.0 64-bit ('Bi_env': venv)",
   "language": "python",
   "name": "python38064bitbienvvenvba07af95a1bb4b078aa8134bba84dff2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
